{
 "cells": [
  {
   "cell_type": "code",
   "id": "initial_id",
   "metadata": {
    "collapsed": true,
    "ExecuteTime": {
     "end_time": "2025-04-09T14:18:47.735559Z",
     "start_time": "2025-04-09T14:18:47.545633Z"
    }
   },
   "source": [
    "import numpy as np\n",
    "import time\n",
    "import matplotlib.pyplot as plt\n",
    "from sklearn.utils import shuffle\n",
    "from sklearn.datasets import make_classification\n",
    "from sklearn.model_selection import train_test_split\n",
    "\n",
    "class Perceptron:\n",
    "    def __init__(self, lr=0.01, epochs=1000):\n",
    "        \"\"\"\n",
    "        初始化感知机模型\n",
    "        :param lr: 学习率\n",
    "        :param epochs: 最大迭代次数\n",
    "        \"\"\"\n",
    "        self.lr = lr\n",
    "        self.epochs = epochs\n",
    "        self.weights = None  # 权重向量\n",
    "        self.bias = 0  # 偏置项\n",
    "        self.loss_history = []  # 损失记录\n",
    "\n",
    "    def _sign(self, x):\n",
    "        \"\"\"\n",
    "        符号函数\n",
    "        :param x: 输入值\n",
    "        :return: 符号值（1 或 -1）\n",
    "        \"\"\"\n",
    "        return 1 if x >= 0 else -1\n",
    "\n",
    "    def fit(self, X, y):\n",
    "        \"\"\"\n",
    "        训练感知机模型\n",
    "        :param X: 输入特征\n",
    "        :param y: 标签\n",
    "        \"\"\"\n",
    "        n_features = X.shape[1]\n",
    "        self.weights = np.zeros(n_features)\n",
    "\n",
    "        for epoch in range(self.epochs):\n",
    "            error_count = 0\n",
    "            for xi, yi in zip(X, y):\n",
    "                output = np.dot(xi, self.weights) + self.bias\n",
    "                prediction = self._sign(output)\n",
    "\n",
    "                if yi * prediction <= 0:\n",
    "                    self.weights += self.lr * yi * xi\n",
    "                    self.bias += self.lr * yi\n",
    "                    error_count += 1\n",
    "\n",
    "            self.loss_history.append(error_count)\n",
    "            if error_count == 0:\n",
    "                break\n",
    "\n",
    "    def predict(self, X):\n",
    "        \"\"\"\n",
    "        预测函数\n",
    "        :param X: 输入特征\n",
    "        :return: 预测结果\n",
    "        \"\"\"\n",
    "        outputs = np.dot(X, self.weights) + self.bias\n",
    "        return np.array([self._sign(x) for x in outputs])"
   ],
   "outputs": [],
   "execution_count": 1
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T14:18:47.745245Z",
     "start_time": "2025-04-09T14:18:47.739574Z"
    }
   },
   "cell_type": "code",
   "source": [
    "def evaluate(y_true, y_pred):\n",
    "    \"\"\"\n",
    "    计算评估指标\n",
    "    :param y_true: 真实标签\n",
    "    :param y_pred: 预测标签\n",
    "    :return: 准确率、精确率、召回率、F1 分数、混淆矩阵\n",
    "    \"\"\"\n",
    "    TP = np.sum((y_true == 1) & (y_pred == 1))\n",
    "    TN = np.sum((y_true == -1) & (y_pred == -1))\n",
    "    FP = np.sum((y_true == -1) & (y_pred == 1))\n",
    "    FN = np.sum((y_true == 1) & (y_pred == -1))\n",
    "\n",
    "    accuracy = (TP + TN) / len(y_true)\n",
    "    precision = TP / (TP + FP) if (TP + FP) != 0 else 0\n",
    "    recall = TP / (TP + FN) if (TP + FN) != 0 else 0\n",
    "    f1 = 2 * (precision * recall) / (precision + recall) if (precision + recall) != 0 else 0\n",
    "    conf_matrix = np.array([[TN, FP], [FN, TP]])\n",
    "\n",
    "    return accuracy, precision, recall, f1, conf_matrix"
   ],
   "id": "9fbbfb47661298ac",
   "outputs": [],
   "execution_count": 2
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T14:18:47.821769Z",
     "start_time": "2025-04-09T14:18:47.808729Z"
    }
   },
   "cell_type": "code",
   "source": [
    "if __name__ == \"__main__\":\n",
    "    # 数据准备\n",
    "    # 使用 make_classification 生成更复杂的数据集\n",
    "    X, y = make_classification(n_samples=500, n_features=2, n_informative=2, n_redundant=0, n_clusters_per_class=1, random_state=42)\n",
    "    y = np.where(y == 0, -1, 1)  # 将标签转换为 {-1, 1}\n",
    "\n",
    "    # 打乱数据\n",
    "    X, y = shuffle(X, y, random_state=42)\n",
    "\n",
    "    # 划分训练集和测试集\n",
    "    X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)"
   ],
   "id": "534a95302732b891",
   "outputs": [],
   "execution_count": 3
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T14:18:47.908614Z",
     "start_time": "2025-04-09T14:18:47.839905Z"
    }
   },
   "cell_type": "code",
   "source": [
    "    # 模型训练\n",
    "    start_time = time.time()\n",
    "    model = Perceptron(lr=0.1, epochs=100)\n",
    "    model.fit(X_train, y_train)\n",
    "    train_time = time.time() - start_time\n",
    "\n",
    "    # 预测评估\n",
    "    y_pred = model.predict(X_test)\n",
    "    acc, prec, rec, f1, cm = evaluate(y_test, y_pred)\n",
    "\n",
    "    # 输出指标\n",
    "    print(f\"准确率: {acc:.4f}\")\n",
    "    print(f\"精确率: {prec:.4f}\")\n",
    "    print(f\"召回率: {rec:.4f}\")\n",
    "    print(f\"F1分数: {f1:.4f}\")\n",
    "    print(f\"训练时间: {train_time:.2f}秒\")\n",
    "    print(\"混淆矩阵:\\n\", cm)"
   ],
   "id": "7215ac23c5c7efbb",
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "准确率: 0.8600\n",
      "精确率: 0.9474\n",
      "召回率: 0.7500\n",
      "F1分数: 0.8372\n",
      "训练时间: 0.06秒\n",
      "混淆矩阵:\n",
      " [[50  2]\n",
      " [12 36]]\n"
     ]
    }
   ],
   "execution_count": 4
  },
  {
   "metadata": {
    "ExecuteTime": {
     "end_time": "2025-04-09T14:18:48.344594Z",
     "start_time": "2025-04-09T14:18:47.933539Z"
    }
   },
   "cell_type": "code",
   "source": [
    "    # 可视化\n",
    "    plt.figure(figsize=(10, 4))\n",
    "\n",
    "    # 指标热度图\n",
    "    plt.subplot(121)\n",
    "    metrics = [acc, prec, rec, f1]\n",
    "    labels = ['Accuracy', 'Precision', 'Recall', 'F1']\n",
    "    plt.imshow([metrics], cmap='YlGnBu', aspect='auto')\n",
    "    plt.colorbar()\n",
    "    plt.xticks(range(4), labels)\n",
    "    plt.title('Performance Metrics Heatmap')\n",
    "\n",
    "    # 决策边界\n",
    "    plt.subplot(122)\n",
    "    x_min, x_max = X[:, 0].min() - 1, X[:, 0].max() + 1\n",
    "    y_min, y_max = X[:, 1].min() - 1, X[:, 1].max() + 1\n",
    "    xx, yy = np.meshgrid(np.linspace(x_min, x_max, 50), np.linspace(y_min, y_max, 50))\n",
    "    Z = model.predict(np.c_[xx.ravel(), yy.ravel()]).reshape(xx.shape)\n",
    "    plt.contourf(xx, yy, Z, alpha=0.4)\n",
    "    plt.scatter(X[:, 0], X[:, 1], c=y, edgecolors='k')\n",
    "    plt.title('Decision Boundary')\n",
    "\n",
    "    plt.tight_layout()\n",
    "    plt.show()"
   ],
   "id": "1eb7ec9cfebd9805",
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<Figure size 1000x400 with 3 Axes>"
      ],
      "image/png": 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"
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "execution_count": 5
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.6"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}
